Pickit 3D 3D Vision Applications Use-Cases

In the assembly process of plastic molded parts, it is challenging to ensure the accurate positioning and orientation of the components, especially when dealing with varying sizes, colors (both matte and glossy), and materials. Traditional assembly methods may lead to errors, inefficiencies, and increased labor costs.

Pickit™ 3D Vision System offers an innovative solution to address the assembly challenges. It automatically detects the exact 3D position, orientation, and dimensions of the plastic molded parts, regardless of their size, color, or material. This system is compatible with a wide range of robot brands, including UR, ABB, Stäubli, KUKA, Fanuc, Hanwha, Yaskawa, Omron, Techman, Nachi, Hyundai, Franka Emika, Aubo, Neuromeka, Doosan, and Siemens PLC, making it highly adaptable to various production setups.

By implementing Pickit™ 3D Vision System for the assembly of plastic molded parts, manufacturers achieve several positive outcomes:

1. Precision: The system ensures precise positioning and orientation of parts, reducing errors and improving product quality.

2. Efficiency: Automation streamlines the assembly process, leading to faster production cycles and increased throughput.

3. Versatility: Pickit™ works with a wide range of robot brands, providing flexibility in adapting to different manufacturing environments and setups.

4. Cost Savings: Reduced labor costs and increased productivity result in cost savings for manufacturers.

5. Reliability: The system's reliability and compatibility with various materials and colors make it a dependable solution for assembly tasks.

In the manual production of shovels, several labor-intensive and repetitive tasks are involved, such as handling wooden handles, attaching grips, and positioning metal blades. These tasks are time-consuming, prone to errors, and often require precision, making them ideal candidates for automation. The challenge is to automate these processes efficiently while ensuring accurate handling of parts of varying sizes and materials.

The solution involves the integration of a cobot equipped with the Pickit 3D vision system and a UR robotic arm to automate the shovel production process:

1. Handling Wooden Handles: Pickit detects and identifies individual wooden handles within a disordered pile and sends precise coordinates to the UR robot. The robot picks each handle and places it in an automatic drill for a hole to be drilled for attaching the grip.

2. Attaching Grips: Pickit locates grips in a disordered bin, and the UR robot picks them based on Pickit's guidance. The robot then screws the grips onto the sides of the long wooden handles with precision.

3. Positioning Metal Blades: Pickit detects the sheet metal blades and provides accurate information to the UR robot. The robot clamps the blades securely onto the other side of the wooden stem.

Implementing the Pickit 3D vision system and UR cobot in the shovel production process leads to several significant outcomes:

1. Increased Efficiency: Automation of handling, drilling, and attaching tasks reduces production time, increases efficiency, and allows for faster shovel manufacturing.

2. Improved Precision: Pickit's precise 3D vision ensures accurate positioning and attachment of handles, grips, and metal blades, reducing errors and improving product quality.

3. Labor Savings: With automation, there is a reduction in the need for manual labor in shovel production, resulting in cost savings and a safer work environment.

4. Versatility: The Pickit system's ability to handle parts of varying sizes, colors, and materials makes it adaptable to different shovel models and configurations.

5. Reliability: The combination of Pickit and UR cobot offers a reliable and consistent production process, minimizing downtimes and ensuring product consistency.

In car body assembly, there is a need for efficiently picking and localizing various parts from semi-structured bins. These bins contain parts of varying sizes, shapes, colors (both matte and glossy), and materials, making manual sorting and placement challenging, time-consuming, and error-prone. The goal is to automate this process while maintaining accuracy and speed.

The solution involves the integration of Pickit™ 3D vision technology with robotic systems to address the challenges in car body assembly:

1. Semi-Structured Bin Picking: Pickit™ is employed to automatically detect and identify parts within semi-structured bins. The system's 3D vision capabilities precisely locate the position, orientation, and dimensions of each part. This information is then relayed to a compatible robot, such as those from UR, ABB, Stäubli, KUKA, Fanuc, Hanwha, Yaskawa, Omron, Techman, Nachi, Hyundai, Franka Emika, Aubo, Neuromeka, Doosan, or Siemens PLC.

2. Part Localizing: Once the parts are picked from the bins, Pickit™ continues to provide real-time guidance to the robot for the accurate placement and localization of each component within the car body assembly. This ensures that each part is precisely positioned and oriented as required for assembly.

Implementing Pickit™ 3D vision technology in car body assembly for semi-structured bin picking and part localizing leads to several positive outcomes:

1. Increased Efficiency: Automation speeds up the bin picking and part localization process, reducing assembly time and improving production throughput.

2. Enhanced Precision: Pickit's 3D vision system ensures accurate positioning and orientation of parts, reducing errors in car body assembly and enhancing product quality.

3. Labor Savings: By automating these tasks, the need for manual labor in sorting and placing parts is significantly reduced, resulting in cost savings.

4. Adaptability: Pickit™ works with a wide range of parts, including those of varying sizes, colors, and materials, making it suitable for various car body assembly configurations.

5. Reliability: The combination of Pickit™ with compatible robotic systems offers a reliable and consistent production process, minimizing assembly errors and disruptions.

The traditional manufacturing processes in the home appliance industry often face challenges related to efficiency, precision, and adaptability to modern technological advancements. There is a need for innovative solutions to enhance production efficiency, reduce errors, and improve the work environment.

LG Home Appliance & Air Solution Company has embraced the Fourth Industrial Revolution technologies, including intelligence and robots, to transform its manufacturing and supply chain operations. Pickit's nine vision systems have been integrated into various aspects of the manufacturing process, including tasks such as door assembly, screw driving, and laser marking.

One specific application of the Pickit 3D vision system is seen in the refrigerator door attachment process. This system precisely guides robots in attaching refrigerator doors, ensuring accurate positioning and alignment. By using Pickit's 3D vision technology, the factory achieves enhanced performance, automation, and safety in its manufacturing operations.

The adoption of Pickit 3D vision technology within LG's Lighthouse Factory has led to several significant outcomes:

1. Increased Efficiency: The integration of Pickit's vision systems streamlines manufacturing processes, leading to higher production efficiency and reduced cycle times.

2. Precision: Pickit's 3D vision ensures precise positioning and alignment, reducing errors in tasks such as door attachment, screw driving, and laser marking.

3. Automation: The use of Pickit technology allows for a higher degree of automation in manufacturing, reducing the reliance on manual labor.

4. Enhanced Safety: By automating tasks with Pickit's guidance, the factory creates a safer work environment by minimizing the risk of accidents and repetitive strain injuries.

5. Competitive Advantage: LG's adoption of Fourth Industrial Revolution technologies, including Pickit, positions the company as a leader in smart home appliance manufacturing and innovation.